<template>
  <div class="mod-demo-echarts">
    <el-alert
      title="提示："
      type="warning"
      :closable="false">
      <div slot-scope="description">
        <p class="el-alert__description">1.
          此Demo只提供ECharts官方使用文档，入门部署和体验功能。具体使用请参考：http://echarts.baidu.com/index.html</p>
      </div>
    </el-alert>

    <el-row :gutter="20">
      <el-col :span="12">
        <el-card>
          <div id="J_chartLineBox" class="chart-box"></div>
        </el-card>
      </el-col>
      <el-col :span="12">
        <el-card>
          <div id="J_chartBarBox" class="chart-box"></div>
        </el-card>
      </el-col>
      <el-col :span="12">
        <el-card>
          <div id="J_chartPieBox" class="chart-box"></div>
        </el-card>
      </el-col>
      <el-col :span="12">
        <el-card>
          <div id="J_chartScatterBox" class="chart-box"></div>
        </el-card>
      </el-col>
      <el-col :span="24">
        <el-card>
          <div id="J_chartMapBox" class="chart-box" style="height: 1080px;"></div>
        </el-card>
      </el-col>
    </el-row>
  </div>
</template>

<script>
  // 引用方式不一样，具体组件需要使用全路径
  // import echarts from 'echarts'

  // require方式引用：具体组件不用写全路径，以echarts目录为基准即可
  // 这是将默认组件全部导入
  let echarts = require('echarts')
  require('echarts/extension/bmap/bmap')

  export default {
    data () {
      return {
        chartLine: null,
        chartBar: null,
        chartPie: null,
        chartScatter: null,
        chartMap: null
      }
    },
    mounted () {
      let ak = 'VHKcqIQ1RlTYc8oNBQxke7tjdBUNUGxn'
      let script = document.createElement('script')
      script.type = 'text/javascript'
      script.src = 'http://api.map.baidu.com/api?v=2.0&ak=' + ak + '&callback=onBMapCallback'
      document.head.appendChild(script)
      this.initChartLine()
      this.initChartBar()
      this.initChartPie()
      this.initChartScatter()
      this.initChartMap()
    },
    activated () {
      // 由于给echart添加了resize事件, 在组件激活时需要重新resize绘画一次, 否则出现空白bug
      if (this.chartLine) {
        this.chartLine.resize()
      }
      if (this.chartBar) {
        this.chartBar.resize()
      }
      if (this.chartPie) {
        this.chartPie.resize()
      }
      if (this.chartScatter) {
        this.chartScatter.resize()
      }
      if (this.chartMap) {
        this.chartMap.resize()
      }
    },
    methods: {
      // 折线图
      initChartLine () {
        var option = {
          'title': {
            'text': '折线图堆叠'
          },
          'tooltip': {
            'trigger': 'axis'
          },
          'legend': {
            'data': ['邮件营销', '联盟广告', '视频广告', '直接访问', '搜索引擎']
          },
          'grid': {
            'left': '3%',
            'right': '4%',
            'bottom': '3%',
            'containLabel': true
          },
          'toolbox': {
            'feature': {
              'saveAsImage': {}
            }
          },
          'xAxis': {
            'type': 'category',
            'boundaryGap': false,
            'data': ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
          },
          'yAxis': {
            'type': 'value'
          },
          'series': [
            {
              'name': '邮件营销',
              'type': 'line',
              'stack': '总量',
              'data': [120, 132, 101, 134, 90, 230, 210]
            },
            {
              'name': '联盟广告',
              'type': 'line',
              'stack': '总量',
              'data': [220, 182, 191, 234, 290, 330, 310]
            },
            {
              'name': '视频广告',
              'type': 'line',
              'stack': '总量',
              'data': [150, 232, 201, 154, 190, 330, 410]
            },
            {
              'name': '直接访问',
              'type': 'line',
              'stack': '总量',
              'data': [320, 332, 301, 334, 390, 330, 320]
            },
            {
              'name': '搜索引擎',
              'type': 'line',
              'stack': '总量',
              'data': [820, 932, 901, 934, 1290, 1330, 1320]
            }
          ]
        }
        this.chartLine = echarts.init(document.getElementById('J_chartLineBox'))
        this.chartLine.setOption(option)
        window.addEventListener('resize', () => {
          this.chartLine.resize()
        })
      },
      // 柱状图
      initChartBar () {
        var option = {
          tooltip: {
            trigger: 'axis',
            axisPointer: {
              type: 'shadow'
            }
          },
          legend: {
            data: ['直接访问', '邮件营销', '联盟广告', '视频广告', '搜索引擎', '百度', '谷歌', '必应', '其他']
          },
          grid: {
            left: '3%',
            right: '4%',
            bottom: '3%',
            containLabel: true
          },
          xAxis: [
            {
              type: 'category',
              data: ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
            }
          ],
          yAxis: [
            {
              type: 'value'
            }
          ],
          series: [
            {
              name: '直接访问',
              type: 'bar',
              data: [320, 332, 301, 334, 390, 330, 320]
            },
            {
              name: '邮件营销',
              type: 'bar',
              stack: '广告',
              data: [120, 132, 101, 134, 90, 230, 210]
            },
            {
              name: '联盟广告',
              type: 'bar',
              stack: '广告',
              data: [220, 182, 191, 234, 290, 330, 310]
            },
            {
              name: '视频广告',
              type: 'bar',
              stack: '广告',
              data: [150, 232, 201, 154, 190, 330, 410]
            },
            {
              name: '搜索引擎',
              type: 'bar',
              data: [862, 1018, 964, 1026, 1679, 1600, 1570],
              markLine: {
                lineStyle: {
                  normal: {
                    type: 'dashed'
                  }
                },
                data: [
                  [{type: 'min'}, {type: 'max'}]
                ]
              }
            },
            {
              name: '百度',
              type: 'bar',
              barWidth: 5,
              stack: '搜索引擎',
              data: [620, 732, 701, 734, 1090, 1130, 1120]
            },
            {
              name: '谷歌',
              type: 'bar',
              stack: '搜索引擎',
              data: [120, 132, 101, 134, 290, 230, 220]
            },
            {
              name: '必应',
              type: 'bar',
              stack: '搜索引擎',
              data: [60, 72, 71, 74, 190, 130, 110]
            },
            {
              name: '其他',
              type: 'bar',
              stack: '搜索引擎',
              data: [62, 82, 91, 84, 109, 110, 120]
            }
          ]
        }
        this.chartBar = echarts.init(document.getElementById('J_chartBarBox'))
        this.chartBar.setOption(option)
        window.addEventListener('resize', () => {
          this.chartBar.resize()
        })
      },
      // 饼状图
      initChartPie () {
        var option = {
          backgroundColor: '#2c343c',
          title: {
            text: 'Customized Pie',
            left: 'center',
            top: 20,
            textStyle: {
              color: '#ccc'
            }
          },
          tooltip: {
            trigger: 'item',
            formatter: '{a} <br/>{b} : {c} ({d}%)'
          },
          visualMap: {
            show: false,
            min: 80,
            max: 600,
            inRange: {
              colorLightness: [0, 1]
            }
          },
          series: [
            {
              name: '访问来源',
              type: 'pie',
              radius: '55%',
              center: ['50%', '50%'],
              data: [
                {value: 335, name: '直接访问'},
                {value: 310, name: '邮件营销'},
                {value: 274, name: '联盟广告'},
                {value: 235, name: '视频广告'},
                {value: 400, name: '搜索引擎'}
              ].sort(function (a, b) {
                return a.value - b.value
              }),
              roseType: 'radius',
              label: {
                normal: {
                  textStyle: {
                    color: 'rgba(255, 255, 255, 0.3)'
                  }
                }
              },
              labelLine: {
                normal: {
                  lineStyle: {
                    color: 'rgba(255, 255, 255, 0.3)'
                  },
                  smooth: 0.2,
                  length: 10,
                  length2: 20
                }
              },
              itemStyle: {
                normal: {
                  color: '#c23531',
                  shadowBlur: 200,
                  shadowColor: 'rgba(0, 0, 0, 0.5)'
                }
              },
              animationType: 'scale',
              animationEasing: 'elasticOut',
              animationDelay: function (idx) {
                return Math.random() * 200
              }
            }
          ]
        }
        this.chartPie = echarts.init(document.getElementById('J_chartPieBox'))
        this.chartPie.setOption(option)
        window.addEventListener('resize', () => {
          this.chartPie.resize()
        })
      },
      // 散点图
      initChartScatter () {
        var option = {
          backgroundColor: new echarts.graphic.RadialGradient(0.3, 0.3, 0.8, [
            {offset: 0, color: '#f7f8fa'},
            {offset: 1, color: '#cdd0d5'}
          ]),
          title: {
            text: '1990 与 2015 年各国家人均寿命与 GDP'
          },
          legend: {
            right: 10,
            data: ['1990', '2015']
          },
          xAxis: {
            splitLine: {
              lineStyle: {
                type: 'dashed'
              }
            }
          },
          yAxis: {
            splitLine: {
              lineStyle: {
                type: 'dashed'
              }
            },
            scale: true
          },
          series: [
            {
              name: '1990',
              data: [
                [28604, 77, 17096869, 'Australia', 1990],
                [31163, 77.4, 27662440, 'Canada', 1990],
                [1516, 68, 1154605773, 'China', 1990],
                [13670, 74.7, 10582082, 'Cuba', 1990],
                [28599, 75, 4986705, 'Finland', 1990],
                [29476, 77.1, 56943299, 'France', 1990],
                [31476, 75.4, 78958237, 'Germany', 1990],
                [28666, 78.1, 254830, 'Iceland', 1990],
                [1777, 57.7, 870601776, 'India', 1990],
                [29550, 79.1, 122249285, 'Japan', 1990],
                [2076, 67.9, 20194354, 'North Korea', 1990],
                [12087, 72, 42972254, 'South Korea', 1990],
                [24021, 75.4, 3397534, 'New Zealand', 1990],
                [43296, 76.8, 4240375, 'Norway', 1990],
                [10088, 70.8, 38195258, 'Poland', 1990],
                [19349, 69.6, 147568552, 'Russia', 1990],
                [10670, 67.3, 53994605, 'Turkey', 1990],
                [26424, 75.7, 57110117, 'United Kingdom', 1990],
                [37062, 75.4, 252847810, 'United States', 1990]
              ],
              type: 'scatter',
              symbolSize: function (data) {
                return Math.sqrt(data[2]) / 5e2
              },
              label: {
                emphasis: {
                  show: true,
                  formatter: function (param) {
                    return param.data[3]
                  },
                  position: 'top'
                }
              },
              itemStyle: {
                normal: {
                  shadowBlur: 10,
                  shadowColor: 'rgba(120, 36, 50, 0.5)',
                  shadowOffsetY: 5,
                  color: new echarts.graphic.RadialGradient(0.4, 0.3, 1, [
                    {offset: 0, color: 'rgb(251, 118, 123)'},
                    {offset: 1, color: 'rgb(204, 46, 72)'}
                  ])
                }
              }
            },
            {
              name: '2015',
              data: [
                [44056, 81.8, 23968973, 'Australia', 2015],
                [43294, 81.7, 35939927, 'Canada', 2015],
                [13334, 76.9, 1376048943, 'China', 2015],
                [21291, 78.5, 11389562, 'Cuba', 2015],
                [38923, 80.8, 5503457, 'Finland', 2015],
                [37599, 81.9, 64395345, 'France', 2015],
                [44053, 81.1, 80688545, 'Germany', 2015],
                [42182, 82.8, 329425, 'Iceland', 2015],
                [5903, 66.8, 1311050527, 'India', 2015],
                [36162, 83.5, 126573481, 'Japan', 2015],
                [1390, 71.4, 25155317, 'North Korea', 2015],
                [34644, 80.7, 50293439, 'South Korea', 2015],
                [34186, 80.6, 4528526, 'New Zealand', 2015],
                [64304, 81.6, 5210967, 'Norway', 2015],
                [24787, 77.3, 38611794, 'Poland', 2015],
                [23038, 73.13, 143456918, 'Russia', 2015],
                [19360, 76.5, 78665830, 'Turkey', 2015],
                [38225, 81.4, 64715810, 'United Kingdom', 2015],
                [53354, 79.1, 321773631, 'United States', 2015]
              ],
              type: 'scatter',
              symbolSize: function (data) {
                return Math.sqrt(data[2]) / 5e2
              },
              label: {
                emphasis: {
                  show: true,
                  formatter: function (param) {
                    return param.data[3]
                  },
                  position: 'top'
                }
              },
              itemStyle: {
                normal: {
                  shadowBlur: 10,
                  shadowColor: 'rgba(25, 100, 150, 0.5)',
                  shadowOffsetY: 5,
                  color: new echarts.graphic.RadialGradient(0.4, 0.3, 1, [
                    {offset: 0, color: 'rgb(129, 227, 238)'},
                    {offset: 1, color: 'rgb(25, 183, 207)'}
                  ])
                }
              }
            }
          ]
        }
        this.chartPie = echarts.init(document.getElementById('J_chartScatterBox'))
        this.chartPie.setOption(option)
        window.addEventListener('resize', () => {
          this.chartPie.resize()
        })
      },
      initChartMap () {
        var data = [
          {name: '海门', value: 9},
          {name: '鄂尔多斯', value: 12},
          {name: '招远', value: 12},
          {name: '舟山', value: 12},
          {name: '齐齐哈尔', value: 14},
          {name: '盐城', value: 15},
          {name: '赤峰', value: 16},
          {name: '青岛', value: 18},
          {name: '乳山', value: 18},
          {name: '金昌', value: 19},
          {name: '泉州', value: 21},
          {name: '莱西', value: 21},
          {name: '日照', value: 21},
          {name: '胶南', value: 22},
          {name: '南通', value: 23},
          {name: '拉萨', value: 24},
          {name: '云浮', value: 24},
          {name: '梅州', value: 25},
          {name: '文登', value: 25},
          {name: '上海', value: 25},
          {name: '攀枝花', value: 25},
          {name: '威海', value: 25},
          {name: '承德', value: 25},
          {name: '厦门', value: 26},
          {name: '汕尾', value: 26},
          {name: '潮州', value: 26},
          {name: '丹东', value: 27},
          {name: '太仓', value: 27},
          {name: '曲靖', value: 27},
          {name: '烟台', value: 28},
          {name: '福州', value: 29},
          {name: '瓦房店', value: 30},
          {name: '即墨', value: 30},
          {name: '抚顺', value: 31},
          {name: '玉溪', value: 31},
          {name: '张家口', value: 31},
          {name: '阳泉', value: 31},
          {name: '莱州', value: 32},
          {name: '湖州', value: 32},
          {name: '汕头', value: 32},
          {name: '昆山', value: 33},
          {name: '宁波', value: 33},
          {name: '湛江', value: 33},
          {name: '揭阳', value: 34},
          {name: '荣成', value: 34},
          {name: '连云港', value: 35},
          {name: '葫芦岛', value: 35},
          {name: '常熟', value: 36},
          {name: '东莞', value: 36},
          {name: '河源', value: 36},
          {name: '淮安', value: 36},
          {name: '泰州', value: 36},
          {name: '南宁', value: 37},
          {name: '营口', value: 37},
          {name: '惠州', value: 37},
          {name: '江阴', value: 37},
          {name: '蓬莱', value: 37},
          {name: '韶关', value: 38},
          {name: '嘉峪关', value: 38},
          {name: '广州', value: 38},
          {name: '延安', value: 38},
          {name: '太原', value: 39},
          {name: '清远', value: 39},
          {name: '中山', value: 39},
          {name: '昆明', value: 39},
          {name: '寿光', value: 40},
          {name: '盘锦', value: 40},
          {name: '长治', value: 41},
          {name: '深圳', value: 41},
          {name: '珠海', value: 42},
          {name: '宿迁', value: 43},
          {name: '咸阳', value: 43},
          {name: '铜川', value: 44},
          {name: '平度', value: 44},
          {name: '佛山', value: 44},
          {name: '海口', value: 44},
          {name: '江门', value: 45},
          {name: '章丘', value: 45},
          {name: '肇庆', value: 46},
          {name: '大连', value: 47},
          {name: '临汾', value: 47},
          {name: '吴江', value: 47},
          {name: '石嘴山', value: 49},
          {name: '沈阳', value: 50},
          {name: '苏州', value: 50},
          {name: '茂名', value: 50},
          {name: '嘉兴', value: 51},
          {name: '长春', value: 51},
          {name: '胶州', value: 52},
          {name: '银川', value: 52},
          {name: '张家港', value: 52},
          {name: '三门峡', value: 53},
          {name: '锦州', value: 54},
          {name: '南昌', value: 54},
          {name: '柳州', value: 54},
          {name: '三亚', value: 54},
          {name: '自贡', value: 56},
          {name: '吉林', value: 56},
          {name: '阳江', value: 57},
          {name: '泸州', value: 57},
          {name: '西宁', value: 57},
          {name: '宜宾', value: 58},
          {name: '呼和浩特', value: 58},
          {name: '成都', value: 58},
          {name: '大同', value: 58},
          {name: '镇江', value: 59},
          {name: '桂林', value: 59},
          {name: '张家界', value: 59},
          {name: '宜兴', value: 59},
          {name: '北海', value: 60},
          {name: '西安', value: 61},
          {name: '金坛', value: 62},
          {name: '东营', value: 62},
          {name: '牡丹江', value: 63},
          {name: '遵义', value: 63},
          {name: '绍兴', value: 63},
          {name: '扬州', value: 64},
          {name: '常州', value: 64},
          {name: '潍坊', value: 65},
          {name: '重庆', value: 66},
          {name: '台州', value: 67},
          {name: '南京', value: 67},
          {name: '滨州', value: 70},
          {name: '贵阳', value: 71},
          {name: '无锡', value: 71},
          {name: '本溪', value: 71},
          {name: '克拉玛依', value: 72},
          {name: '渭南', value: 72},
          {name: '马鞍山', value: 72},
          {name: '宝鸡', value: 72},
          {name: '焦作', value: 75},
          {name: '句容', value: 75},
          {name: '北京', value: 79},
          {name: '徐州', value: 79},
          {name: '衡水', value: 80},
          {name: '包头', value: 80},
          {name: '绵阳', value: 80},
          {name: '乌鲁木齐', value: 84},
          {name: '枣庄', value: 84},
          {name: '杭州', value: 84},
          {name: '淄博', value: 85},
          {name: '鞍山', value: 86},
          {name: '溧阳', value: 86},
          {name: '库尔勒', value: 86},
          {name: '安阳', value: 90},
          {name: '开封', value: 90},
          {name: '济南', value: 92},
          {name: '德阳', value: 93},
          {name: '温州', value: 95},
          {name: '九江', value: 96},
          {name: '邯郸', value: 98},
          {name: '临安', value: 99},
          {name: '兰州', value: 99},
          {name: '沧州', value: 100},
          {name: '临沂', value: 103},
          {name: '南充', value: 104},
          {name: '天津', value: 105},
          {name: '富阳', value: 106},
          {name: '泰安', value: 112},
          {name: '诸暨', value: 112},
          {name: '郑州', value: 113},
          {name: '哈尔滨', value: 114},
          {name: '聊城', value: 116},
          {name: '芜湖', value: 117},
          {name: '唐山', value: 119},
          {name: '平顶山', value: 119},
          {name: '邢台', value: 119},
          {name: '德州', value: 120},
          {name: '济宁', value: 120},
          {name: '荆州', value: 127},
          {name: '宜昌', value: 130},
          {name: '义乌', value: 132},
          {name: '丽水', value: 133},
          {name: '洛阳', value: 134},
          {name: '秦皇岛', value: 136},
          {name: '株洲', value: 143},
          {name: '石家庄', value: 147},
          {name: '莱芜', value: 148},
          {name: '常德', value: 152},
          {name: '保定', value: 153},
          {name: '湘潭', value: 154},
          {name: '金华', value: 157},
          {name: '岳阳', value: 169},
          {name: '长沙', value: 175},
          {name: '衢州', value: 177},
          {name: '廊坊', value: 193},
          {name: '菏泽', value: 194},
          {name: '合肥', value: 229},
          {name: '武汉', value: 273},
          {name: '大庆', value: 279}
        ]
        var geoCoordMap = {
          '海门': [121.15, 31.89],
          '鄂尔多斯': [109.781327, 39.608266],
          '招远': [120.38, 37.35],
          '舟山': [122.207216, 29.985295],
          '齐齐哈尔': [123.97, 47.33],
          '盐城': [120.13, 33.38],
          '赤峰': [118.87, 42.28],
          '青岛': [120.33, 36.07],
          '乳山': [121.52, 36.89],
          '金昌': [102.188043, 38.520089],
          '泉州': [118.58, 24.93],
          '莱西': [120.53, 36.86],
          '日照': [119.46, 35.42],
          '胶南': [119.97, 35.88],
          '南通': [121.05, 32.08],
          '拉萨': [91.11, 29.97],
          '云浮': [112.02, 22.93],
          '梅州': [116.1, 24.55],
          '文登': [122.05, 37.2],
          '上海': [121.48, 31.22],
          '攀枝花': [101.718637, 26.582347],
          '威海': [122.1, 37.5],
          '承德': [117.93, 40.97],
          '厦门': [118.1, 24.46],
          '汕尾': [115.375279, 22.786211],
          '潮州': [116.63, 23.68],
          '丹东': [124.37, 40.13],
          '太仓': [121.1, 31.45],
          '曲靖': [103.79, 25.51],
          '烟台': [121.39, 37.52],
          '福州': [119.3, 26.08],
          '瓦房店': [121.979603, 39.627114],
          '即墨': [120.45, 36.38],
          '抚顺': [123.97, 41.97],
          '玉溪': [102.52, 24.35],
          '张家口': [114.87, 40.82],
          '阳泉': [113.57, 37.85],
          '莱州': [119.942327, 37.177017],
          '湖州': [120.1, 30.86],
          '汕头': [116.69, 23.39],
          '昆山': [120.95, 31.39],
          '宁波': [121.56, 29.86],
          '湛江': [110.359377, 21.270708],
          '揭阳': [116.35, 23.55],
          '荣成': [122.41, 37.16],
          '连云港': [119.16, 34.59],
          '葫芦岛': [120.836932, 40.711052],
          '常熟': [120.74, 31.64],
          '东莞': [113.75, 23.04],
          '河源': [114.68, 23.73],
          '淮安': [119.15, 33.5],
          '泰州': [119.9, 32.49],
          '南宁': [108.33, 22.84],
          '营口': [122.18, 40.65],
          '惠州': [114.4, 23.09],
          '江阴': [120.26, 31.91],
          '蓬莱': [120.75, 37.8],
          '韶关': [113.62, 24.84],
          '嘉峪关': [98.289152, 39.77313],
          '广州': [113.23, 23.16],
          '延安': [109.47, 36.6],
          '太原': [112.53, 37.87],
          '清远': [113.01, 23.7],
          '中山': [113.38, 22.52],
          '昆明': [102.73, 25.04],
          '寿光': [118.73, 36.86],
          '盘锦': [122.070714, 41.119997],
          '长治': [113.08, 36.18],
          '深圳': [114.07, 22.62],
          '珠海': [113.52, 22.3],
          '宿迁': [118.3, 33.96],
          '咸阳': [108.72, 34.36],
          '铜川': [109.11, 35.09],
          '平度': [119.97, 36.77],
          '佛山': [113.11, 23.05],
          '海口': [110.35, 20.02],
          '江门': [113.06, 22.61],
          '章丘': [117.53, 36.72],
          '肇庆': [112.44, 23.05],
          '大连': [121.62, 38.92],
          '临汾': [111.5, 36.08],
          '吴江': [120.63, 31.16],
          '石嘴山': [106.39, 39.04],
          '沈阳': [123.38, 41.8],
          '苏州': [120.62, 31.32],
          '茂名': [110.88, 21.68],
          '嘉兴': [120.76, 30.77],
          '长春': [125.35, 43.88],
          '胶州': [120.03336, 36.264622],
          '银川': [106.27, 38.47],
          '张家港': [120.555821, 31.875428],
          '三门峡': [111.19, 34.76],
          '锦州': [121.15, 41.13],
          '南昌': [115.89, 28.68],
          '柳州': [109.4, 24.33],
          '三亚': [109.511909, 18.252847],
          '自贡': [104.778442, 29.33903],
          '吉林': [126.57, 43.87],
          '阳江': [111.95, 21.85],
          '泸州': [105.39, 28.91],
          '西宁': [101.74, 36.56],
          '宜宾': [104.56, 29.77],
          '呼和浩特': [111.65, 40.82],
          '成都': [104.06, 30.67],
          '大同': [113.3, 40.12],
          '镇江': [119.44, 32.2],
          '桂林': [110.28, 25.29],
          '张家界': [110.479191, 29.117096],
          '宜兴': [119.82, 31.36],
          '北海': [109.12, 21.49],
          '西安': [108.95, 34.27],
          '金坛': [119.56, 31.74],
          '东营': [118.49, 37.46],
          '牡丹江': [129.58, 44.6],
          '遵义': [106.9, 27.7],
          '绍兴': [120.58, 30.01],
          '扬州': [119.42, 32.39],
          '常州': [119.95, 31.79],
          '潍坊': [119.1, 36.62],
          '重庆': [106.54, 29.59],
          '台州': [121.420757, 28.656386],
          '南京': [118.78, 32.04],
          '滨州': [118.03, 37.36],
          '贵阳': [106.71, 26.57],
          '无锡': [120.29, 31.59],
          '本溪': [123.73, 41.3],
          '克拉玛依': [84.77, 45.59],
          '渭南': [109.5, 34.52],
          '马鞍山': [118.48, 31.56],
          '宝鸡': [107.15, 34.38],
          '焦作': [113.21, 35.24],
          '句容': [119.16, 31.95],
          '北京': [116.46, 39.92],
          '徐州': [117.2, 34.26],
          '衡水': [115.72, 37.72],
          '包头': [110, 40.58],
          '绵阳': [104.73, 31.48],
          '乌鲁木齐': [87.68, 43.77],
          '枣庄': [117.57, 34.86],
          '杭州': [120.19, 30.26],
          '淄博': [118.05, 36.78],
          '鞍山': [122.85, 41.12],
          '溧阳': [119.48, 31.43],
          '库尔勒': [86.06, 41.68],
          '安阳': [114.35, 36.1],
          '开封': [114.35, 34.79],
          '济南': [117, 36.65],
          '德阳': [104.37, 31.13],
          '温州': [120.65, 28.01],
          '九江': [115.97, 29.71],
          '邯郸': [114.47, 36.6],
          '临安': [119.72, 30.23],
          '兰州': [103.73, 36.03],
          '沧州': [116.83, 38.33],
          '临沂': [118.35, 35.05],
          '南充': [106.110698, 30.837793],
          '天津': [117.2, 39.13],
          '富阳': [119.95, 30.07],
          '泰安': [117.13, 36.18],
          '诸暨': [120.23, 29.71],
          '郑州': [113.65, 34.76],
          '哈尔滨': [126.63, 45.75],
          '聊城': [115.97, 36.45],
          '芜湖': [118.38, 31.33],
          '唐山': [118.02, 39.63],
          '平顶山': [113.29, 33.75],
          '邢台': [114.48, 37.05],
          '德州': [116.29, 37.45],
          '济宁': [116.59, 35.38],
          '荆州': [112.239741, 30.335165],
          '宜昌': [111.3, 30.7],
          '义乌': [120.06, 29.32],
          '丽水': [119.92, 28.45],
          '洛阳': [112.44, 34.7],
          '秦皇岛': [119.57, 39.95],
          '株洲': [113.16, 27.83],
          '石家庄': [114.48, 38.03],
          '莱芜': [117.67, 36.19],
          '常德': [111.69, 29.05],
          '保定': [115.48, 38.85],
          '湘潭': [112.91, 27.87],
          '金华': [119.64, 29.12],
          '岳阳': [113.09, 29.37],
          '长沙': [113, 28.21],
          '衢州': [118.88, 28.97],
          '廊坊': [116.7, 39.53],
          '菏泽': [115.480656, 35.23375],
          '合肥': [117.27, 31.86],
          '武汉': [114.31, 30.52],
          '大庆': [125.03, 46.58]
        }

        var convertData = function (data) {
          var res = []
          for (var i = 0; i < data.length; i++) {
            var geoCoord = geoCoordMap[data[i].name]
            if (geoCoord) {
              res.push({
                name: data[i].name,
                value: geoCoord.concat(data[i].value)
              })
            }
          }
          return res
        }

        let option = {
          title: {
            text: '全国主要城市空气质量 - 百度地图',
            subtext: 'data from PM25.in',
            sublink: 'http://www.pm25.in',
            left: 'center'
          },
          tooltip: {
            trigger: 'item'
          },
          bmap: {
            center: [104.114129, 37.550339],
            zoom: 5,
            roam: true,
            mapStyle: {
              styleJson: [{
                'featureType': 'water',
                'elementType': 'all',
                'stylers': {
                  'color': '#d1d1d1'
                }
              }, {
                'featureType': 'land',
                'elementType': 'all',
                'stylers': {
                  'color': '#f3f3f3'
                }
              }, {
                'featureType': 'railway',
                'elementType': 'all',
                'stylers': {
                  'visibility': 'off'
                }
              }, {
                'featureType': 'highway',
                'elementType': 'all',
                'stylers': {
                  'color': '#fdfdfd'
                }
              }, {
                'featureType': 'highway',
                'elementType': 'labels',
                'stylers': {
                  'visibility': 'off'
                }
              }, {
                'featureType': 'arterial',
                'elementType': 'geometry',
                'stylers': {
                  'color': '#fefefe'
                }
              }, {
                'featureType': 'arterial',
                'elementType': 'geometry.fill',
                'stylers': {
                  'color': '#fefefe'
                }
              }, {
                'featureType': 'poi',
                'elementType': 'all',
                'stylers': {
                  'visibility': 'off'
                }
              }, {
                'featureType': 'green',
                'elementType': 'all',
                'stylers': {
                  'visibility': 'off'
                }
              }, {
                'featureType': 'subway',
                'elementType': 'all',
                'stylers': {
                  'visibility': 'off'
                }
              }, {
                'featureType': 'manmade',
                'elementType': 'all',
                'stylers': {
                  'color': '#d1d1d1'
                }
              }, {
                'featureType': 'local',
                'elementType': 'all',
                'stylers': {
                  'color': '#d1d1d1'
                }
              }, {
                'featureType': 'arterial',
                'elementType': 'labels',
                'stylers': {
                  'visibility': 'off'
                }
              }, {
                'featureType': 'boundary',
                'elementType': 'all',
                'stylers': {
                  'color': '#fefefe'
                }
              }, {
                'featureType': 'building',
                'elementType': 'all',
                'stylers': {
                  'color': '#d1d1d1'
                }
              }, {
                'featureType': 'label',
                'elementType': 'labels.text.fill',
                'stylers': {
                  'color': '#999999'
                }
              }]
            }
          },
          series: [
            {
              name: 'pm2.5',
              type: 'scatter',
              coordinateSystem: 'bmap',
              data: convertData(data),
              symbolSize: function (val) {
                return val[2] / 10
              },
              label: {
                normal: {
                  formatter: '{b}',
                  position: 'right',
                  show: false
                },
                emphasis: {
                  show: true
                }
              },
              itemStyle: {
                normal: {
                  color: 'purple'
                }
              }
            },
            {
              name: 'Top 5',
              type: 'effectScatter',
              coordinateSystem: 'bmap',
              data: convertData(data.sort(function (a, b) {
                return b.value - a.value
              }).slice(0, 6)),
              symbolSize: function (val) {
                return val[2] / 10
              },
              showEffectOn: 'render',
              rippleEffect: {
                brushType: 'stroke'
              },
              hoverAnimation: true,
              label: {
                normal: {
                  formatter: '{b}',
                  position: 'right',
                  show: true
                }
              },
              itemStyle: {
                normal: {
                  color: 'purple',
                  shadowBlur: 10,
                  shadowColor: '#333'
                }
              },
              zlevel: 1
            }
          ]
        }
        this.chartMap = echarts.init(document.getElementById('J_chartMapBox'))
        this.chartMap.setOption(option)
        window.addEventListener('resize', () => {
          this.chartMap.resize()
        })
      }
    }
  }
</script>

<style lang="scss">
  .mod-demo-echarts {
    > .el-alert {
      margin-bottom: 10px;
    }
    > .el-row {
      margin-top: -10px;
      margin-bottom: -10px;
      .el-col {
        padding-top: 10px;
        padding-bottom: 10px;
      }
    }
    .chart-box {
      min-height: 400px;
      width: 100%;
    }
  }
</style>
